TY - GEN
T1 - Virtual power plant energy optimisation in smart grids
AU - Dzobo, Oliver
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5/1
Y1 - 2019/5/1
N2 - The growing number of distributed renewable energy sources connected to the grid has brought some challenges to the management of the power system network. New optimisation models are required to manage these distributed generation units when they are clustered together. In this case, virtual power plants (VPPs) plays an important role by ensuring that the value of the produced power by clusters of distributed power generation units is efficiently managed. In this paper, an optimisation model based on mixed integer programming technique for the management of clusters of distributed generation units consisting of local heat and power supply system with CHPs, solar photovoltaic systems and thermal power generation units is presented. The proposed algorithm ensures maximum benefit of thermal and electric energy in the power system network. The results show that there is a 10% increase in benefit when virtual power plants are used and optimised.
AB - The growing number of distributed renewable energy sources connected to the grid has brought some challenges to the management of the power system network. New optimisation models are required to manage these distributed generation units when they are clustered together. In this case, virtual power plants (VPPs) plays an important role by ensuring that the value of the produced power by clusters of distributed power generation units is efficiently managed. In this paper, an optimisation model based on mixed integer programming technique for the management of clusters of distributed generation units consisting of local heat and power supply system with CHPs, solar photovoltaic systems and thermal power generation units is presented. The proposed algorithm ensures maximum benefit of thermal and electric energy in the power system network. The results show that there is a 10% increase in benefit when virtual power plants are used and optimised.
KW - load demand
KW - optimisation
KW - solar photovoltaic
KW - virtual power plants
UR - http://www.scopus.com/inward/record.url?scp=85065822278&partnerID=8YFLogxK
U2 - 10.1109/RoboMech.2019.8704830
DO - 10.1109/RoboMech.2019.8704830
M3 - Conference contribution
AN - SCOPUS:85065822278
T3 - Proceedings - 2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2019
SP - 714
EP - 718
BT - Proceedings - 2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2019
Y2 - 28 January 2019 through 30 January 2019
ER -